Using the Alternative Five Factor Personality Model to Explain Driving Anger Expression

1. Using the Alternative Five Factor Personality Model to Explain Driving Anger Expression Paul Sârbescu¹’², Iuliana Costea¹, Silvia Rusu¹ ¹West University, Bld. V. Pârvan nr. 4, Timişoara, 300233, Romania ²Bucharest University, Bld. M. Kogălniceanu nr. 34-36, 050107, Romania Abstract Results (continued) In the second step, the five personality factors of the AFFM were added as predictors; of this, the only significant predictor was Agg-Host (β = .40, p < .01). The personality factors add an extra 17,7% (ΔR² = .177, p < .01) to the model’s explanatory potential. In the second step, age (β = -.15, p < .05) and driving frequency (β = .17, p < .05) remain significant predictors of DAE. Thus, DAE can be explained by demographic variables and personality factors of the AFFM at a rate of 27,7% (R² = .277). Table 2. Hierarchical regression analysis results for DAE This research sought to identify the role that the Alternative Five Factor Personality Model (AFFM) has in explaining driving anger expression. The non-experimental research was performed on a sample of 230 participants, aged between 20 and 40 years, using the Zuckerman-Kuhlman Personality Questionnaire (ZKPQ) and the Driving Anger Expression Inventory (DAX). The results indicate that driving anger expression can be explained at a rate of approximately 28% by demographic variables (age, gender, mileage and driving frequency) and the AFFM personality factors. The personality factor with topmost explanatory potential was Aggression-Hostility. The results are analyzed in relation to previous research in this field, and directions for further research are suggested. Introduction Road accidents cause many deaths and severe injuries in Romania. The last report of the European Traffic Safety Council (ETSC, 2010) designates Romania as the number one European country, regarding the annual number of deaths from road accidents per million inhabitants (130). Also, while other countries (Latvia, Spain, Portugal and Estonia) recorded reductions in road deaths of over 50% in comparison with the year 2001, Romania and Malta are the only countries which recorded an increase in road deaths of almost 15%. Several studies in the traffic and transportation research field have concluded that the human factor is responsible for 85-90% of road accidents (Jonah, 1997; Iverson & Rundmo, 2002). Because of this fact, many studies have focused on the relationship between human factors and road accidents; their findings state that risky driving and driving anger are the main predictors of road accidents (Chliaoutakis, Demakakos, Tzamalouka, Bakou, Koumaki & Darviri, 2002; Dahlen, Martin, Ragan & Kuhlman, 2005; Dahlen & White, 2006). In Romania, many studies have focused on the links between personality and risky driving behavior or road accidents, but very few considered driving anger or the expression of driving anger into account. The present study analyzed the utility of the AFFM in explaining driving anger expression. Discussion The present study analyzed the utility of the AFFM in explaining driving anger expression. The results supported AFFM’s potential in explaining DAE, especially through the strong relation between Agg-Host and DAE, also identified by other authors (Dahlen & White, 2006; Schwebel et. all, 2006). Surprisingly, none of the other personality factors had a significant explanatory potential, although ImpSS correlated positively with DAE. Thus, it would seem that future research is required, in order to verify the possible links between AFFM and driving anger, or even the propensity for angry driving. The present research has some limitations. Firstly, the overwhelming majority of male participants might have an impact on research results. Although in Romania most drivers are males (thus there is a similarity between the research sample and the population), the ratio is not as unbalanced as it is in this research. Future research could use a more balanced sample, in order to provide a more accurate understanding of the relationship between the AFFM and DAE. Secondly, no measure of social desirability was applied, thereby the participants’ social desirability level is unknown. Although social desirability doesn't seem to have a negative impact on traffic and transportation research (Lajunen & Summala, 2003; Sullman & Taylor, 2010), further research could use a measure of it, in order to possibly exclude the high social desirability level participants from the research sample. Methods Participants The total sample (n = 230) consisted of 209 males (90.9%) and 21 females (9.1%). The age of the respondents ranged from 20 to 40 years (M = 27.36, SD = 4.92). The sample consisted mostly of students, their friends and relatives. All subjects volunteered to take part in the study. Measures and procedures The participants completed the Zuckerman-Kuhlman Personality Questionnaire (ZKPQ) (Zuckerman et. all, 1993) and the Driving Anger Expression Inventory (Deffenbacher et. all, 2002). Also, data regarding age, gender, mileage and driving frequency were collected. Conclusions Results In conclusion, the results of this study support the Alternative Five Factor Model’s potential in explaining driving anger expression. It appears that Aggression-Hostility is the most powerful predictor of DAE, although Impulsive Sensation Seeking presented a positive (but weak) association with it. Overall, the results are in accordance with previous research in this field, supporting the use of the AFFM in traffic and transportation research. Table 1 presents the correlation matrix of the variables used in this research: Table 1. Correlations among research variables References Chliaoutakis, J.E., Demakakos, P., Tzamalouka, G., Bakou, V., Koumaki, M., Darviri, C. (2002). Aggressive behavior while driving as predictor of self-reported car crashes. Journal of Safety Research, 33(4), 431–443. Dahlen, E.R., Martin, R.C., Ragan, K., Kuhlman, M.M. (2005). Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving. Accident Analysis and Prevention, 37, 341–348. Dahlen, E., White, R. (2006). The Big Five factors, sensation seeking, and driving anger in the prediction of unsafe driving. Personality and Individual Differences, 41, 903–915. Deffenbacher, J. L., Lynch, R. S., Oetting, E. R., & Swaim, R. C. (2002). The Driving Anger Expression Inventory: A measure of how people express their anger on the road. Behaviour Research and Therapy, 40, 717−737. Deffenbacher, J.L., Deffenbacher, D.M., Lynch, R.S., Richards, T.L. (2003). Anger, aggression, and risky behavior: a comparison of high and low anger drivers. Behaviour Research and Therapy, 41(6), 701–718. European Traffic Safety Council (2010). Road Safety Target in Sight: Making up for lost time. 4th Road Safety Pin Report. Found at: http://www.etsc.eu. Iversen, H., Rundmo, T. (2002). Personality, risky driving and accident involvement among norwegian drivers. Personality and Individual Differences, 33, 1251–1263. Jonah, B.A. (1997). Sensation seeking and risky driving: A review and synthesis of the literature. Accident Analysis and Prevention, 29(5), 651−665. Lajunen, T., Summala, H. (2003). Can we trust self-reports of driving? Effects of impression management on driver behaviour questionnaire responses. Transportation Research Part F: Traffic Psychology and Behaviour, 6(2), 97–107. McCrae, R.R. & Costa, P.T. (1987). Validation of the Five-Factor Model of Personality Across Instruments and Observers. Journal of Personality and Social Psychology, 52(1), 81-90. Schwebel, D.C., Severson, J., Ball, K.K., Rizzo, M. (2006). Individual difference factors in risky driving: the roles of anger/hostility, conscientiousness, and sensation-seeking. Accident Analysis & Prevention, 38, 801–810. Sullman, M. J. M., & Taylor, J. E. (2010). Social desirability and self-reported driving behaviours: Should we be worried? Transportation Research Part F: Traffic Psychology and Behaviour, 13(3), 215-221. Zuckerman, M., Kuhlman, D. M., Joireman, J., Teta, P., & Kraft, M. (1993). A comparison of three structural models for personality: The big three, the big five, and the alternative five. Journal of Personality and Social Psychology, 65, 757–768. As expected, the AFFM factor which showed the strongest correlation with driving anger expression was Agg-Host (.45). ImpSS also positively correlated with DAE, but at a lower intensity (.20). None of the other factors showed significant correlations with DAE. Table 2 presents the results of the hierarchical multiple regression using DAE as the dependent variable. The results in show that the only significant predictors of DAE in step 1 were age (β = -.21, p < .01) and driving frequency (β = .24, p < .01). The model based on age, gender, mileage and driving frequency explained DAE at a rate of 10% (R² = .10).